{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 收入增长与房价增长对比\n",
    "1. 有一个传说，程序员的收入是跟房价一起增长的，那么我们拿历史数据来分析一下吧。\n",
    "2. 收入数据来自国家统计局官网 www.stats.gov.cn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#加载收入数据\n",
    "import pandas as pd\n",
    "income = pd.read_csv('otherdata/收入数据.csv', index_col = 0)\n",
    "income.index = [x[:-1] for x in income.index]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#加载北京房价数据并计算每年均价\n",
    "from common import read\n",
    "df = read('北京')\n",
    "df['year'] = [x[:4] for x in df['成交时间']]\n",
    "housePrice = df.groupby('year')['成交价(元/平)'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "#2010年之前成交量太少，房价数据不可靠\n",
    "housePriceDf = pd.DataFrame({'北京房价':housePrice.loc[housePrice.index>='2011']})\n",
    "data = housePriceDf.merge(income, left_index = True, right_index = True, how = 'inner')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/matplotlib/font_manager.py:1328: UserWarning: findfont: Font family ['sans-serif'] not found. Falling back to DejaVu Sans\n",
      "  (prop.get_family(), self.defaultFamily[fontext]))\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#北京房价相对涨幅与收入相对涨幅对比\n",
    "import os\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "from matplotlib.font_manager import FontProperties\n",
    "font=FontProperties(fname='font/Songti.ttc',size=18)\n",
    "title = '房价收入对比'\n",
    "columns = ['北京房价', '城镇单位就业人员平均工资(元)', \n",
    "           '信息传输、计算机服务和软件业城镇单位就业人员平均工资(元)','金融业城镇单位就业人员平均工资(元)']\n",
    "plt.rcParams['font.sans-serif']=['SimHei']\n",
    "matplotlib.rc('font', size=18)\n",
    "matplotlib.rcParams['figure.figsize'] = [15, 10]\n",
    "for col in columns:\n",
    "    plt.plot(data[col]/data[col].iloc[0])\n",
    "plt.legend(columns, prop = font)\n",
    "plt.grid(True)\n",
    "plt.title(title, fontproperties = font)\n",
    "#重画x轴\n",
    "dir_name = os.path.join('fig', '房价收入分析')\n",
    "if not os.path.exists(dir_name):\n",
    "    os.makedirs(dir_name)\n",
    "plt.savefig(os.path.join(dir_name, title +'.png'))\n",
    "plt.show()\n",
    "plt.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "城镇单位就业人员平均工资(元)\n",
       "批发和零售业城镇单位就业人员平均工资(元)             3.378618\n",
       "农、林、牧、渔业城镇单位就业人员平均工资(元)           3.365354\n",
       "教育城镇单位就业人员平均工资(元)                 3.219546\n",
       "卫生、社会保障和社会福利业城镇单位就业人员平均工资(元)      3.214112\n",
       "制造业城镇单位就业人员平均工资(元)                3.048241\n",
       "建筑业城镇单位就业人员平均工资(元)                3.006601\n",
       "城镇单位就业人员平均工资(元)                   3.006270\n",
       "租赁和商务服务业城镇单位就业人员平均工资(元)           2.927069\n",
       "公共管理和社会组织城镇单位就业人员平均工资(元)          2.898273\n",
       "文化、体育和娱乐业城镇单位就业人员平均工资(元)          2.885409\n",
       "交通运输、仓储和邮政业城镇单位就业人员平均工资(元)        2.875139\n",
       "水利、环境和公共设施管理业城镇单位就业人员平均工资(元)      2.841158\n",
       "科学研究、技术服务和地质勘查业城镇单位就业人员平均工资(元)    2.805345\n",
       "信息传输、计算机服务和软件业城镇单位就业人员平均工资(元)     2.791405\n",
       "金融业城镇单位就业人员平均工资(元)                2.791370\n",
       "电力、燃气及水的生产和供应业城镇单位就业人员平均工资(元)     2.699373\n",
       "住宿和餐饮业城镇单位就业人员平均工资(元)             2.683973\n",
       "房地产业城镇单位就业人员平均工资(元)               2.655818\n",
       "居民服务和其他服务业城镇单位就业人员平均工资(元)         2.481689\n",
       "采矿业城镇单位就业人员平均工资(元)                2.465851\n",
       "dtype: float64"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#分析一下各行业涨幅对比\n",
    "rise_ratio = income.loc['2017']/income.loc['2007']\n",
    "rise_ratio.sort_values(ascending = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/matplotlib/font_manager.py:1328: UserWarning: findfont: Font family ['sans-serif'] not found. Falling back to DejaVu Sans\n",
      "  (prop.get_family(), self.defaultFamily[fontext]))\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#金融与IT对比\n",
    "font=FontProperties(fname='font/Songti.ttc',size=18)\n",
    "title = '金融与IT收入对比'\n",
    "columns = ['信息传输、计算机服务和软件业城镇单位就业人员平均工资(元)','金融业城镇单位就业人员平均工资(元)']\n",
    "plt.rcParams['font.sans-serif']=['SimHei']\n",
    "matplotlib.rc('font', size=18)\n",
    "matplotlib.rcParams['figure.figsize'] = [15, 10]\n",
    "for col in columns:\n",
    "    plt.plot(income[col])\n",
    "plt.legend(columns, prop = font)\n",
    "plt.grid(True)\n",
    "plt.title(title, fontproperties = font)\n",
    "#重画x轴\n",
    "dir_name = os.path.join('fig', '房价收入分析')\n",
    "if not os.path.exists(dir_name):\n",
    "    os.makedirs(dir_name)\n",
    "plt.savefig(os.path.join(dir_name, title +'.png'))\n",
    "plt.show()\n",
    "plt.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/pandas/core/indexing.py:189: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>城镇单位就业人员平均工资(元)</th>\n",
       "      <th>农、林、牧、渔业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>采矿业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>制造业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>电力、燃气及水的生产和供应业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>建筑业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>交通运输、仓储和邮政业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>信息传输、计算机服务和软件业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>批发和零售业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>住宿和餐饮业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>金融业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>房地产业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>租赁和商务服务业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>科学研究、技术服务和地质勘查业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>水利、环境和公共设施管理业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>居民服务和其他服务业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>教育城镇单位就业人员平均工资(元)</th>\n",
       "      <th>卫生、社会保障和社会福利业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>文化、体育和娱乐业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>公共管理和社会组织城镇单位就业人员平均工资(元)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>16.1%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>14.2%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>12.9%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>14.0%</td>\n",
       "      <td>8.9%</td>\n",
       "      <td>23.1%</td>\n",
       "      <td>12.5%</td>\n",
       "      <td>16.0%</td>\n",
       "      <td>11.0%</td>\n",
       "      <td>14.7%</td>\n",
       "      <td>8.3%</td>\n",
       "      <td>19.4%</td>\n",
       "      <td>12.7%</td>\n",
       "      <td>16.9%</td>\n",
       "      <td>8.1%</td>\n",
       "      <td>10.0%</td>\n",
       "      <td>14.2%</td>\n",
       "      <td>9.4%</td>\n",
       "      <td>8.0%</td>\n",
       "      <td>13.4%</td>\n",
       "      <td>13.6%</td>\n",
       "      <td>20.0%</td>\n",
       "      <td>13.1%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>14.3%</td>\n",
       "      <td>9.5%</td>\n",
       "      <td>21.9%</td>\n",
       "      <td>11.8%</td>\n",
       "      <td>14.9%</td>\n",
       "      <td>12.2%</td>\n",
       "      <td>15.7%</td>\n",
       "      <td>16.0%</td>\n",
       "      <td>17.2%</td>\n",
       "      <td>10.0%</td>\n",
       "      <td>20.3%</td>\n",
       "      <td>9.7%</td>\n",
       "      <td>13.4%</td>\n",
       "      <td>16.3%</td>\n",
       "      <td>11.2%</td>\n",
       "      <td>15.1%</td>\n",
       "      <td>13.5%</td>\n",
       "      <td>13.2%</td>\n",
       "      <td>10.5%</td>\n",
       "      <td>16.5%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>14.6%</td>\n",
       "      <td>12.9%</td>\n",
       "      <td>18.0%</td>\n",
       "      <td>14.4%</td>\n",
       "      <td>14.8%</td>\n",
       "      <td>14.5%</td>\n",
       "      <td>15.3%</td>\n",
       "      <td>11.9%</td>\n",
       "      <td>16.6%</td>\n",
       "      <td>9.8%</td>\n",
       "      <td>21.4%</td>\n",
       "      <td>9.8%</td>\n",
       "      <td>15.4%</td>\n",
       "      <td>16.5%</td>\n",
       "      <td>9.1%</td>\n",
       "      <td>14.5%</td>\n",
       "      <td>14.6%</td>\n",
       "      <td>13.4%</td>\n",
       "      <td>14.0%</td>\n",
       "      <td>11.4%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>18.5%</td>\n",
       "      <td>17.0%</td>\n",
       "      <td>16.8%</td>\n",
       "      <td>16.0%</td>\n",
       "      <td>17.8%</td>\n",
       "      <td>14.3%</td>\n",
       "      <td>15.7%</td>\n",
       "      <td>9.8%</td>\n",
       "      <td>18.4%</td>\n",
       "      <td>11.9%</td>\n",
       "      <td>24.0%</td>\n",
       "      <td>17.3%</td>\n",
       "      <td>13.5%</td>\n",
       "      <td>21.5%</td>\n",
       "      <td>17.6%</td>\n",
       "      <td>13.0%</td>\n",
       "      <td>23.9%</td>\n",
       "      <td>18.2%</td>\n",
       "      <td>17.7%</td>\n",
       "      <td>23.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>16.9%</td>\n",
       "      <td>15.8%</td>\n",
       "      <td>21.5%</td>\n",
       "      <td>15.4%</td>\n",
       "      <td>15.1%</td>\n",
       "      <td>14.8%</td>\n",
       "      <td>14.8%</td>\n",
       "      <td>15.1%</td>\n",
       "      <td>22.5%</td>\n",
       "      <td>13.3%</td>\n",
       "      <td>22.5%</td>\n",
       "      <td>15.5%</td>\n",
       "      <td>18.4%</td>\n",
       "      <td>18.4%</td>\n",
       "      <td>14.8%</td>\n",
       "      <td>12.2%</td>\n",
       "      <td>15.1%</td>\n",
       "      <td>15.4%</td>\n",
       "      <td>12.3%</td>\n",
       "      <td>16.5%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>11.6%</td>\n",
       "      <td>14.3%</td>\n",
       "      <td>11.1%</td>\n",
       "      <td>9.9%</td>\n",
       "      <td>8.7%</td>\n",
       "      <td>13.8%</td>\n",
       "      <td>10.2%</td>\n",
       "      <td>5.9%</td>\n",
       "      <td>12.9%</td>\n",
       "      <td>8.0%</td>\n",
       "      <td>12.1%</td>\n",
       "      <td>7.1%</td>\n",
       "      <td>7.8%</td>\n",
       "      <td>10.2%</td>\n",
       "      <td>9.7%</td>\n",
       "      <td>10.1%</td>\n",
       "      <td>15.8%</td>\n",
       "      <td>10.8%</td>\n",
       "      <td>10.5%</td>\n",
       "      <td>9.4%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>13.3%</td>\n",
       "      <td>16.4%</td>\n",
       "      <td>16.2%</td>\n",
       "      <td>15.3%</td>\n",
       "      <td>13.0%</td>\n",
       "      <td>13.9%</td>\n",
       "      <td>14.6%</td>\n",
       "      <td>10.8%</td>\n",
       "      <td>15.4%</td>\n",
       "      <td>12.1%</td>\n",
       "      <td>16.1%</td>\n",
       "      <td>11.3%</td>\n",
       "      <td>11.5%</td>\n",
       "      <td>12.4%</td>\n",
       "      <td>10.3%</td>\n",
       "      <td>12.1%</td>\n",
       "      <td>12.8%</td>\n",
       "      <td>12.8%</td>\n",
       "      <td>9.7%</td>\n",
       "      <td>8.3%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>14.4%</td>\n",
       "      <td>16.5%</td>\n",
       "      <td>18.2%</td>\n",
       "      <td>18.6%</td>\n",
       "      <td>11.4%</td>\n",
       "      <td>16.6%</td>\n",
       "      <td>16.3%</td>\n",
       "      <td>10.1%</td>\n",
       "      <td>20.9%</td>\n",
       "      <td>17.6%</td>\n",
       "      <td>15.6%</td>\n",
       "      <td>19.4%</td>\n",
       "      <td>18.7%</td>\n",
       "      <td>14.0%</td>\n",
       "      <td>13.0%</td>\n",
       "      <td>17.6%</td>\n",
       "      <td>10.8%</td>\n",
       "      <td>14.8%</td>\n",
       "      <td>15.6%</td>\n",
       "      <td>10.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>11.9%</td>\n",
       "      <td>16.5%</td>\n",
       "      <td>9.0%</td>\n",
       "      <td>13.6%</td>\n",
       "      <td>10.4%</td>\n",
       "      <td>13.6%</td>\n",
       "      <td>13.4%</td>\n",
       "      <td>13.5%</td>\n",
       "      <td>14.0%</td>\n",
       "      <td>13.8%</td>\n",
       "      <td>10.6%</td>\n",
       "      <td>9.2%</td>\n",
       "      <td>13.2%</td>\n",
       "      <td>7.8%</td>\n",
       "      <td>12.0%</td>\n",
       "      <td>5.9%</td>\n",
       "      <td>10.5%</td>\n",
       "      <td>13.8%</td>\n",
       "      <td>11.9%</td>\n",
       "      <td>9.5%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>10.1%</td>\n",
       "      <td>13.8%</td>\n",
       "      <td>5.6%</td>\n",
       "      <td>11.5%</td>\n",
       "      <td>15.3%</td>\n",
       "      <td>15.3%</td>\n",
       "      <td>8.6%</td>\n",
       "      <td>12.9%</td>\n",
       "      <td>8.6%</td>\n",
       "      <td>8.9%</td>\n",
       "      <td>11.0%</td>\n",
       "      <td>9.2%</td>\n",
       "      <td>17.6%</td>\n",
       "      <td>10.6%</td>\n",
       "      <td>11.7%</td>\n",
       "      <td>9.4%</td>\n",
       "      <td>8.8%</td>\n",
       "      <td>10.3%</td>\n",
       "      <td>10.8%</td>\n",
       "      <td>6.9%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>9.5%</td>\n",
       "      <td>9.8%</td>\n",
       "      <td>2.6%</td>\n",
       "      <td>10.6%</td>\n",
       "      <td>9.3%</td>\n",
       "      <td>8.9%</td>\n",
       "      <td>9.4%</td>\n",
       "      <td>10.9%</td>\n",
       "      <td>11.0%</td>\n",
       "      <td>9.5%</td>\n",
       "      <td>8.7%</td>\n",
       "      <td>8.9%</td>\n",
       "      <td>7.3%</td>\n",
       "      <td>7.4%</td>\n",
       "      <td>8.5%</td>\n",
       "      <td>9.0%</td>\n",
       "      <td>8.9%</td>\n",
       "      <td>9.1%</td>\n",
       "      <td>8.5%</td>\n",
       "      <td>7.8%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>10.1%</td>\n",
       "      <td>12.7%</td>\n",
       "      <td>-3.7%</td>\n",
       "      <td>7.7%</td>\n",
       "      <td>7.6%</td>\n",
       "      <td>6.7%</td>\n",
       "      <td>8.5%</td>\n",
       "      <td>11.1%</td>\n",
       "      <td>8.0%</td>\n",
       "      <td>9.5%</td>\n",
       "      <td>6.0%</td>\n",
       "      <td>8.4%</td>\n",
       "      <td>8.0%</td>\n",
       "      <td>8.7%</td>\n",
       "      <td>11.0%</td>\n",
       "      <td>7.0%</td>\n",
       "      <td>17.7%</td>\n",
       "      <td>13.2%</td>\n",
       "      <td>13.0%</td>\n",
       "      <td>17.3%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>8.9%</td>\n",
       "      <td>5.2%</td>\n",
       "      <td>1.9%</td>\n",
       "      <td>7.5%</td>\n",
       "      <td>6.3%</td>\n",
       "      <td>6.5%</td>\n",
       "      <td>7.0%</td>\n",
       "      <td>9.3%</td>\n",
       "      <td>7.8%</td>\n",
       "      <td>6.3%</td>\n",
       "      <td>2.3%</td>\n",
       "      <td>8.7%</td>\n",
       "      <td>5.9%</td>\n",
       "      <td>8.1%</td>\n",
       "      <td>9.7%</td>\n",
       "      <td>6.2%</td>\n",
       "      <td>11.9%</td>\n",
       "      <td>11.7%</td>\n",
       "      <td>9.8%</td>\n",
       "      <td>13.9%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>10.0%</td>\n",
       "      <td>8.6%</td>\n",
       "      <td>14.8%</td>\n",
       "      <td>8.4%</td>\n",
       "      <td>7.7%</td>\n",
       "      <td>6.7%</td>\n",
       "      <td>8.9%</td>\n",
       "      <td>8.7%</td>\n",
       "      <td>9.4%</td>\n",
       "      <td>5.5%</td>\n",
       "      <td>4.6%</td>\n",
       "      <td>5.8%</td>\n",
       "      <td>6.0%</td>\n",
       "      <td>11.6%</td>\n",
       "      <td>9.4%</td>\n",
       "      <td>6.3%</td>\n",
       "      <td>12.0%</td>\n",
       "      <td>12.0%</td>\n",
       "      <td>9.9%</td>\n",
       "      <td>13.3%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>11.0%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     城镇单位就业人员平均工资(元) 农、林、牧、渔业城镇单位就业人员平均工资(元) 采矿业城镇单位就业人员平均工资(元)  \\\n",
       "1999             NaN                     NaN                NaN   \n",
       "2000            nan%                    nan%               nan%   \n",
       "2001           16.1%                    nan%               nan%   \n",
       "2002           14.2%                    nan%               nan%   \n",
       "2003           12.9%                    nan%               nan%   \n",
       "2004           14.0%                    8.9%              23.1%   \n",
       "2005           14.3%                    9.5%              21.9%   \n",
       "2006           14.6%                   12.9%              18.0%   \n",
       "2007           18.5%                   17.0%              16.8%   \n",
       "2008           16.9%                   15.8%              21.5%   \n",
       "2009           11.6%                   14.3%              11.1%   \n",
       "2010           13.3%                   16.4%              16.2%   \n",
       "2011           14.4%                   16.5%              18.2%   \n",
       "2012           11.9%                   16.5%               9.0%   \n",
       "2013           10.1%                   13.8%               5.6%   \n",
       "2014            9.5%                    9.8%               2.6%   \n",
       "2015           10.1%                   12.7%              -3.7%   \n",
       "2016            8.9%                    5.2%               1.9%   \n",
       "2017           10.0%                    8.6%              14.8%   \n",
       "2018           11.0%                    nan%               nan%   \n",
       "\n",
       "     制造业城镇单位就业人员平均工资(元) 电力、燃气及水的生产和供应业城镇单位就业人员平均工资(元) 建筑业城镇单位就业人员平均工资(元)  \\\n",
       "1999                NaN                           NaN                NaN   \n",
       "2000               nan%                          nan%               nan%   \n",
       "2001               nan%                          nan%               nan%   \n",
       "2002               nan%                          nan%               nan%   \n",
       "2003               nan%                          nan%               nan%   \n",
       "2004              12.5%                         16.0%              11.0%   \n",
       "2005              11.8%                         14.9%              12.2%   \n",
       "2006              14.4%                         14.8%              14.5%   \n",
       "2007              16.0%                         17.8%              14.3%   \n",
       "2008              15.4%                         15.1%              14.8%   \n",
       "2009               9.9%                          8.7%              13.8%   \n",
       "2010              15.3%                         13.0%              13.9%   \n",
       "2011              18.6%                         11.4%              16.6%   \n",
       "2012              13.6%                         10.4%              13.6%   \n",
       "2013              11.5%                         15.3%              15.3%   \n",
       "2014              10.6%                          9.3%               8.9%   \n",
       "2015               7.7%                          7.6%               6.7%   \n",
       "2016               7.5%                          6.3%               6.5%   \n",
       "2017               8.4%                          7.7%               6.7%   \n",
       "2018               nan%                          nan%               nan%   \n",
       "\n",
       "     交通运输、仓储和邮政业城镇单位就业人员平均工资(元) 信息传输、计算机服务和软件业城镇单位就业人员平均工资(元)  \\\n",
       "1999                        NaN                           NaN   \n",
       "2000                       nan%                          nan%   \n",
       "2001                       nan%                          nan%   \n",
       "2002                       nan%                          nan%   \n",
       "2003                       nan%                          nan%   \n",
       "2004                      14.7%                          8.3%   \n",
       "2005                      15.7%                         16.0%   \n",
       "2006                      15.3%                         11.9%   \n",
       "2007                      15.7%                          9.8%   \n",
       "2008                      14.8%                         15.1%   \n",
       "2009                      10.2%                          5.9%   \n",
       "2010                      14.6%                         10.8%   \n",
       "2011                      16.3%                         10.1%   \n",
       "2012                      13.4%                         13.5%   \n",
       "2013                       8.6%                         12.9%   \n",
       "2014                       9.4%                         10.9%   \n",
       "2015                       8.5%                         11.1%   \n",
       "2016                       7.0%                          9.3%   \n",
       "2017                       8.9%                          8.7%   \n",
       "2018                       nan%                          nan%   \n",
       "\n",
       "     批发和零售业城镇单位就业人员平均工资(元) 住宿和餐饮业城镇单位就业人员平均工资(元) 金融业城镇单位就业人员平均工资(元)  \\\n",
       "1999                   NaN                   NaN                NaN   \n",
       "2000                  nan%                  nan%               nan%   \n",
       "2001                  nan%                  nan%               nan%   \n",
       "2002                  nan%                  nan%               nan%   \n",
       "2003                  nan%                  nan%               nan%   \n",
       "2004                 19.4%                 12.7%              16.9%   \n",
       "2005                 17.2%                 10.0%              20.3%   \n",
       "2006                 16.6%                  9.8%              21.4%   \n",
       "2007                 18.4%                 11.9%              24.0%   \n",
       "2008                 22.5%                 13.3%              22.5%   \n",
       "2009                 12.9%                  8.0%              12.1%   \n",
       "2010                 15.4%                 12.1%              16.1%   \n",
       "2011                 20.9%                 17.6%              15.6%   \n",
       "2012                 14.0%                 13.8%              10.6%   \n",
       "2013                  8.6%                  8.9%              11.0%   \n",
       "2014                 11.0%                  9.5%               8.7%   \n",
       "2015                  8.0%                  9.5%               6.0%   \n",
       "2016                  7.8%                  6.3%               2.3%   \n",
       "2017                  9.4%                  5.5%               4.6%   \n",
       "2018                  nan%                  nan%               nan%   \n",
       "\n",
       "     房地产业城镇单位就业人员平均工资(元) 租赁和商务服务业城镇单位就业人员平均工资(元)  \\\n",
       "1999                 NaN                     NaN   \n",
       "2000                nan%                    nan%   \n",
       "2001                nan%                    nan%   \n",
       "2002                nan%                    nan%   \n",
       "2003                nan%                    nan%   \n",
       "2004                8.1%                   10.0%   \n",
       "2005                9.7%                   13.4%   \n",
       "2006                9.8%                   15.4%   \n",
       "2007               17.3%                   13.5%   \n",
       "2008               15.5%                   18.4%   \n",
       "2009                7.1%                    7.8%   \n",
       "2010               11.3%                   11.5%   \n",
       "2011               19.4%                   18.7%   \n",
       "2012                9.2%                   13.2%   \n",
       "2013                9.2%                   17.6%   \n",
       "2014                8.9%                    7.3%   \n",
       "2015                8.4%                    8.0%   \n",
       "2016                8.7%                    5.9%   \n",
       "2017                5.8%                    6.0%   \n",
       "2018                nan%                    nan%   \n",
       "\n",
       "     科学研究、技术服务和地质勘查业城镇单位就业人员平均工资(元) 水利、环境和公共设施管理业城镇单位就业人员平均工资(元)  \\\n",
       "1999                            NaN                          NaN   \n",
       "2000                           nan%                         nan%   \n",
       "2001                           nan%                         nan%   \n",
       "2002                           nan%                         nan%   \n",
       "2003                           nan%                         nan%   \n",
       "2004                          14.2%                         9.4%   \n",
       "2005                          16.3%                        11.2%   \n",
       "2006                          16.5%                         9.1%   \n",
       "2007                          21.5%                        17.6%   \n",
       "2008                          18.4%                        14.8%   \n",
       "2009                          10.2%                         9.7%   \n",
       "2010                          12.4%                        10.3%   \n",
       "2011                          14.0%                        13.0%   \n",
       "2012                           7.8%                        12.0%   \n",
       "2013                          10.6%                        11.7%   \n",
       "2014                           7.4%                         8.5%   \n",
       "2015                           8.7%                        11.0%   \n",
       "2016                           8.1%                         9.7%   \n",
       "2017                          11.6%                         9.4%   \n",
       "2018                           nan%                         nan%   \n",
       "\n",
       "     居民服务和其他服务业城镇单位就业人员平均工资(元) 教育城镇单位就业人员平均工资(元) 卫生、社会保障和社会福利业城镇单位就业人员平均工资(元)  \\\n",
       "1999                       NaN               NaN                          NaN   \n",
       "2000                      nan%              nan%                         nan%   \n",
       "2001                      nan%              nan%                         nan%   \n",
       "2002                      nan%              nan%                         nan%   \n",
       "2003                      nan%              nan%                         nan%   \n",
       "2004                      8.0%             13.4%                        13.6%   \n",
       "2005                     15.1%             13.5%                        13.2%   \n",
       "2006                     14.5%             14.6%                        13.4%   \n",
       "2007                     13.0%             23.9%                        18.2%   \n",
       "2008                     12.2%             15.1%                        15.4%   \n",
       "2009                     10.1%             15.8%                        10.8%   \n",
       "2010                     12.1%             12.8%                        12.8%   \n",
       "2011                     17.6%             10.8%                        14.8%   \n",
       "2012                      5.9%             10.5%                        13.8%   \n",
       "2013                      9.4%              8.8%                        10.3%   \n",
       "2014                      9.0%              8.9%                         9.1%   \n",
       "2015                      7.0%             17.7%                        13.2%   \n",
       "2016                      6.2%             11.9%                        11.7%   \n",
       "2017                      6.3%             12.0%                        12.0%   \n",
       "2018                      nan%              nan%                         nan%   \n",
       "\n",
       "     文化、体育和娱乐业城镇单位就业人员平均工资(元) 公共管理和社会组织城镇单位就业人员平均工资(元)  \n",
       "1999                      NaN                      NaN  \n",
       "2000                     nan%                     nan%  \n",
       "2001                     nan%                     nan%  \n",
       "2002                     nan%                     nan%  \n",
       "2003                     nan%                     nan%  \n",
       "2004                    20.0%                    13.1%  \n",
       "2005                    10.5%                    16.5%  \n",
       "2006                    14.0%                    11.4%  \n",
       "2007                    17.7%                    23.0%  \n",
       "2008                    12.3%                    16.5%  \n",
       "2009                    10.5%                     9.4%  \n",
       "2010                     9.7%                     8.3%  \n",
       "2011                    15.6%                    10.0%  \n",
       "2012                    11.9%                     9.5%  \n",
       "2013                    10.8%                     6.9%  \n",
       "2014                     8.5%                     7.8%  \n",
       "2015                    13.0%                    17.3%  \n",
       "2016                     9.8%                    13.9%  \n",
       "2017                     9.9%                    13.3%  \n",
       "2018                     nan%                     nan%  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rise = income.copy()\n",
    "for col in rise.columns:\n",
    "    for i in range(len(rise) - 1):\n",
    "        rise[col].iloc[i+1] = '%.1f%%'%((income[col].iloc[i+1]/income[col].iloc[i]-1) * 100)\n",
    "rise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>城镇单位就业人员平均工资(元)</th>\n",
       "      <th>信息传输、计算机服务和软件业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>金融业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>卫生、社会保障和社会福利业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>制造业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>农、林、牧、渔业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>租赁和商务服务业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>居民服务和其他服务业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>公共管理和社会组织城镇单位就业人员平均工资(元)</th>\n",
       "      <th>文化、体育和娱乐业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>教育城镇单位就业人员平均工资(元)</th>\n",
       "      <th>水利、环境和公共设施管理业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>交通运输、仓储和邮政业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>房地产业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>电力、燃气及水的生产和供应业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>建筑业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>住宿和餐饮业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>批发和零售业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>采矿业城镇单位就业人员平均工资(元)</th>\n",
       "      <th>科学研究、技术服务和地质勘查业城镇单位就业人员平均工资(元)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>14.0%</td>\n",
       "      <td>8.3%</td>\n",
       "      <td>16.9%</td>\n",
       "      <td>13.6%</td>\n",
       "      <td>12.5%</td>\n",
       "      <td>8.9%</td>\n",
       "      <td>10.0%</td>\n",
       "      <td>8.0%</td>\n",
       "      <td>13.1%</td>\n",
       "      <td>20.0%</td>\n",
       "      <td>13.4%</td>\n",
       "      <td>9.4%</td>\n",
       "      <td>14.7%</td>\n",
       "      <td>8.1%</td>\n",
       "      <td>16.0%</td>\n",
       "      <td>11.0%</td>\n",
       "      <td>12.7%</td>\n",
       "      <td>19.4%</td>\n",
       "      <td>23.1%</td>\n",
       "      <td>14.2%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>14.3%</td>\n",
       "      <td>16.0%</td>\n",
       "      <td>20.3%</td>\n",
       "      <td>13.2%</td>\n",
       "      <td>11.8%</td>\n",
       "      <td>9.5%</td>\n",
       "      <td>13.4%</td>\n",
       "      <td>15.1%</td>\n",
       "      <td>16.5%</td>\n",
       "      <td>10.5%</td>\n",
       "      <td>13.5%</td>\n",
       "      <td>11.2%</td>\n",
       "      <td>15.7%</td>\n",
       "      <td>9.7%</td>\n",
       "      <td>14.9%</td>\n",
       "      <td>12.2%</td>\n",
       "      <td>10.0%</td>\n",
       "      <td>17.2%</td>\n",
       "      <td>21.9%</td>\n",
       "      <td>16.3%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>14.6%</td>\n",
       "      <td>11.9%</td>\n",
       "      <td>21.4%</td>\n",
       "      <td>13.4%</td>\n",
       "      <td>14.4%</td>\n",
       "      <td>12.9%</td>\n",
       "      <td>15.4%</td>\n",
       "      <td>14.5%</td>\n",
       "      <td>11.4%</td>\n",
       "      <td>14.0%</td>\n",
       "      <td>14.6%</td>\n",
       "      <td>9.1%</td>\n",
       "      <td>15.3%</td>\n",
       "      <td>9.8%</td>\n",
       "      <td>14.8%</td>\n",
       "      <td>14.5%</td>\n",
       "      <td>9.8%</td>\n",
       "      <td>16.6%</td>\n",
       "      <td>18.0%</td>\n",
       "      <td>16.5%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>18.5%</td>\n",
       "      <td>9.8%</td>\n",
       "      <td>24.0%</td>\n",
       "      <td>18.2%</td>\n",
       "      <td>16.0%</td>\n",
       "      <td>17.0%</td>\n",
       "      <td>13.5%</td>\n",
       "      <td>13.0%</td>\n",
       "      <td>23.0%</td>\n",
       "      <td>17.7%</td>\n",
       "      <td>23.9%</td>\n",
       "      <td>17.6%</td>\n",
       "      <td>15.7%</td>\n",
       "      <td>17.3%</td>\n",
       "      <td>17.8%</td>\n",
       "      <td>14.3%</td>\n",
       "      <td>11.9%</td>\n",
       "      <td>18.4%</td>\n",
       "      <td>16.8%</td>\n",
       "      <td>21.5%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>16.9%</td>\n",
       "      <td>15.1%</td>\n",
       "      <td>22.5%</td>\n",
       "      <td>15.4%</td>\n",
       "      <td>15.4%</td>\n",
       "      <td>15.8%</td>\n",
       "      <td>18.4%</td>\n",
       "      <td>12.2%</td>\n",
       "      <td>16.5%</td>\n",
       "      <td>12.3%</td>\n",
       "      <td>15.1%</td>\n",
       "      <td>14.8%</td>\n",
       "      <td>14.8%</td>\n",
       "      <td>15.5%</td>\n",
       "      <td>15.1%</td>\n",
       "      <td>14.8%</td>\n",
       "      <td>13.3%</td>\n",
       "      <td>22.5%</td>\n",
       "      <td>21.5%</td>\n",
       "      <td>18.4%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>11.6%</td>\n",
       "      <td>5.9%</td>\n",
       "      <td>12.1%</td>\n",
       "      <td>10.8%</td>\n",
       "      <td>9.9%</td>\n",
       "      <td>14.3%</td>\n",
       "      <td>7.8%</td>\n",
       "      <td>10.1%</td>\n",
       "      <td>9.4%</td>\n",
       "      <td>10.5%</td>\n",
       "      <td>15.8%</td>\n",
       "      <td>9.7%</td>\n",
       "      <td>10.2%</td>\n",
       "      <td>7.1%</td>\n",
       "      <td>8.7%</td>\n",
       "      <td>13.8%</td>\n",
       "      <td>8.0%</td>\n",
       "      <td>12.9%</td>\n",
       "      <td>11.1%</td>\n",
       "      <td>10.2%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>13.3%</td>\n",
       "      <td>10.8%</td>\n",
       "      <td>16.1%</td>\n",
       "      <td>12.8%</td>\n",
       "      <td>15.3%</td>\n",
       "      <td>16.4%</td>\n",
       "      <td>11.5%</td>\n",
       "      <td>12.1%</td>\n",
       "      <td>8.3%</td>\n",
       "      <td>9.7%</td>\n",
       "      <td>12.8%</td>\n",
       "      <td>10.3%</td>\n",
       "      <td>14.6%</td>\n",
       "      <td>11.3%</td>\n",
       "      <td>13.0%</td>\n",
       "      <td>13.9%</td>\n",
       "      <td>12.1%</td>\n",
       "      <td>15.4%</td>\n",
       "      <td>16.2%</td>\n",
       "      <td>12.4%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>14.4%</td>\n",
       "      <td>10.1%</td>\n",
       "      <td>15.6%</td>\n",
       "      <td>14.8%</td>\n",
       "      <td>18.6%</td>\n",
       "      <td>16.5%</td>\n",
       "      <td>18.7%</td>\n",
       "      <td>17.6%</td>\n",
       "      <td>10.0%</td>\n",
       "      <td>15.6%</td>\n",
       "      <td>10.8%</td>\n",
       "      <td>13.0%</td>\n",
       "      <td>16.3%</td>\n",
       "      <td>19.4%</td>\n",
       "      <td>11.4%</td>\n",
       "      <td>16.6%</td>\n",
       "      <td>17.6%</td>\n",
       "      <td>20.9%</td>\n",
       "      <td>18.2%</td>\n",
       "      <td>14.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>11.9%</td>\n",
       "      <td>13.5%</td>\n",
       "      <td>10.6%</td>\n",
       "      <td>13.8%</td>\n",
       "      <td>13.6%</td>\n",
       "      <td>16.5%</td>\n",
       "      <td>13.2%</td>\n",
       "      <td>5.9%</td>\n",
       "      <td>9.5%</td>\n",
       "      <td>11.9%</td>\n",
       "      <td>10.5%</td>\n",
       "      <td>12.0%</td>\n",
       "      <td>13.4%</td>\n",
       "      <td>9.2%</td>\n",
       "      <td>10.4%</td>\n",
       "      <td>13.6%</td>\n",
       "      <td>13.8%</td>\n",
       "      <td>14.0%</td>\n",
       "      <td>9.0%</td>\n",
       "      <td>7.8%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>10.1%</td>\n",
       "      <td>12.9%</td>\n",
       "      <td>11.0%</td>\n",
       "      <td>10.3%</td>\n",
       "      <td>11.5%</td>\n",
       "      <td>13.8%</td>\n",
       "      <td>17.6%</td>\n",
       "      <td>9.4%</td>\n",
       "      <td>6.9%</td>\n",
       "      <td>10.8%</td>\n",
       "      <td>8.8%</td>\n",
       "      <td>11.7%</td>\n",
       "      <td>8.6%</td>\n",
       "      <td>9.2%</td>\n",
       "      <td>15.3%</td>\n",
       "      <td>15.3%</td>\n",
       "      <td>8.9%</td>\n",
       "      <td>8.6%</td>\n",
       "      <td>5.6%</td>\n",
       "      <td>10.6%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>9.5%</td>\n",
       "      <td>10.9%</td>\n",
       "      <td>8.7%</td>\n",
       "      <td>9.1%</td>\n",
       "      <td>10.6%</td>\n",
       "      <td>9.8%</td>\n",
       "      <td>7.3%</td>\n",
       "      <td>9.0%</td>\n",
       "      <td>7.8%</td>\n",
       "      <td>8.5%</td>\n",
       "      <td>8.9%</td>\n",
       "      <td>8.5%</td>\n",
       "      <td>9.4%</td>\n",
       "      <td>8.9%</td>\n",
       "      <td>9.3%</td>\n",
       "      <td>8.9%</td>\n",
       "      <td>9.5%</td>\n",
       "      <td>11.0%</td>\n",
       "      <td>2.6%</td>\n",
       "      <td>7.4%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>10.1%</td>\n",
       "      <td>11.1%</td>\n",
       "      <td>6.0%</td>\n",
       "      <td>13.2%</td>\n",
       "      <td>7.7%</td>\n",
       "      <td>12.7%</td>\n",
       "      <td>8.0%</td>\n",
       "      <td>7.0%</td>\n",
       "      <td>17.3%</td>\n",
       "      <td>13.0%</td>\n",
       "      <td>17.7%</td>\n",
       "      <td>11.0%</td>\n",
       "      <td>8.5%</td>\n",
       "      <td>8.4%</td>\n",
       "      <td>7.6%</td>\n",
       "      <td>6.7%</td>\n",
       "      <td>9.5%</td>\n",
       "      <td>8.0%</td>\n",
       "      <td>-3.7%</td>\n",
       "      <td>8.7%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>8.9%</td>\n",
       "      <td>9.3%</td>\n",
       "      <td>2.3%</td>\n",
       "      <td>11.7%</td>\n",
       "      <td>7.5%</td>\n",
       "      <td>5.2%</td>\n",
       "      <td>5.9%</td>\n",
       "      <td>6.2%</td>\n",
       "      <td>13.9%</td>\n",
       "      <td>9.8%</td>\n",
       "      <td>11.9%</td>\n",
       "      <td>9.7%</td>\n",
       "      <td>7.0%</td>\n",
       "      <td>8.7%</td>\n",
       "      <td>6.3%</td>\n",
       "      <td>6.5%</td>\n",
       "      <td>6.3%</td>\n",
       "      <td>7.8%</td>\n",
       "      <td>1.9%</td>\n",
       "      <td>8.1%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>10.0%</td>\n",
       "      <td>8.7%</td>\n",
       "      <td>4.6%</td>\n",
       "      <td>12.0%</td>\n",
       "      <td>8.4%</td>\n",
       "      <td>8.6%</td>\n",
       "      <td>6.0%</td>\n",
       "      <td>6.3%</td>\n",
       "      <td>13.3%</td>\n",
       "      <td>9.9%</td>\n",
       "      <td>12.0%</td>\n",
       "      <td>9.4%</td>\n",
       "      <td>8.9%</td>\n",
       "      <td>5.8%</td>\n",
       "      <td>7.7%</td>\n",
       "      <td>6.7%</td>\n",
       "      <td>5.5%</td>\n",
       "      <td>9.4%</td>\n",
       "      <td>14.8%</td>\n",
       "      <td>11.6%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>11.0%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "      <td>nan%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     城镇单位就业人员平均工资(元) 信息传输、计算机服务和软件业城镇单位就业人员平均工资(元) 金融业城镇单位就业人员平均工资(元)  \\\n",
       "2004           14.0%                          8.3%              16.9%   \n",
       "2005           14.3%                         16.0%              20.3%   \n",
       "2006           14.6%                         11.9%              21.4%   \n",
       "2007           18.5%                          9.8%              24.0%   \n",
       "2008           16.9%                         15.1%              22.5%   \n",
       "2009           11.6%                          5.9%              12.1%   \n",
       "2010           13.3%                         10.8%              16.1%   \n",
       "2011           14.4%                         10.1%              15.6%   \n",
       "2012           11.9%                         13.5%              10.6%   \n",
       "2013           10.1%                         12.9%              11.0%   \n",
       "2014            9.5%                         10.9%               8.7%   \n",
       "2015           10.1%                         11.1%               6.0%   \n",
       "2016            8.9%                          9.3%               2.3%   \n",
       "2017           10.0%                          8.7%               4.6%   \n",
       "2018           11.0%                          nan%               nan%   \n",
       "\n",
       "     卫生、社会保障和社会福利业城镇单位就业人员平均工资(元) 制造业城镇单位就业人员平均工资(元) 农、林、牧、渔业城镇单位就业人员平均工资(元)  \\\n",
       "2004                        13.6%              12.5%                    8.9%   \n",
       "2005                        13.2%              11.8%                    9.5%   \n",
       "2006                        13.4%              14.4%                   12.9%   \n",
       "2007                        18.2%              16.0%                   17.0%   \n",
       "2008                        15.4%              15.4%                   15.8%   \n",
       "2009                        10.8%               9.9%                   14.3%   \n",
       "2010                        12.8%              15.3%                   16.4%   \n",
       "2011                        14.8%              18.6%                   16.5%   \n",
       "2012                        13.8%              13.6%                   16.5%   \n",
       "2013                        10.3%              11.5%                   13.8%   \n",
       "2014                         9.1%              10.6%                    9.8%   \n",
       "2015                        13.2%               7.7%                   12.7%   \n",
       "2016                        11.7%               7.5%                    5.2%   \n",
       "2017                        12.0%               8.4%                    8.6%   \n",
       "2018                         nan%               nan%                    nan%   \n",
       "\n",
       "     租赁和商务服务业城镇单位就业人员平均工资(元) 居民服务和其他服务业城镇单位就业人员平均工资(元)  \\\n",
       "2004                   10.0%                      8.0%   \n",
       "2005                   13.4%                     15.1%   \n",
       "2006                   15.4%                     14.5%   \n",
       "2007                   13.5%                     13.0%   \n",
       "2008                   18.4%                     12.2%   \n",
       "2009                    7.8%                     10.1%   \n",
       "2010                   11.5%                     12.1%   \n",
       "2011                   18.7%                     17.6%   \n",
       "2012                   13.2%                      5.9%   \n",
       "2013                   17.6%                      9.4%   \n",
       "2014                    7.3%                      9.0%   \n",
       "2015                    8.0%                      7.0%   \n",
       "2016                    5.9%                      6.2%   \n",
       "2017                    6.0%                      6.3%   \n",
       "2018                    nan%                      nan%   \n",
       "\n",
       "     公共管理和社会组织城镇单位就业人员平均工资(元) 文化、体育和娱乐业城镇单位就业人员平均工资(元) 教育城镇单位就业人员平均工资(元)  \\\n",
       "2004                    13.1%                    20.0%             13.4%   \n",
       "2005                    16.5%                    10.5%             13.5%   \n",
       "2006                    11.4%                    14.0%             14.6%   \n",
       "2007                    23.0%                    17.7%             23.9%   \n",
       "2008                    16.5%                    12.3%             15.1%   \n",
       "2009                     9.4%                    10.5%             15.8%   \n",
       "2010                     8.3%                     9.7%             12.8%   \n",
       "2011                    10.0%                    15.6%             10.8%   \n",
       "2012                     9.5%                    11.9%             10.5%   \n",
       "2013                     6.9%                    10.8%              8.8%   \n",
       "2014                     7.8%                     8.5%              8.9%   \n",
       "2015                    17.3%                    13.0%             17.7%   \n",
       "2016                    13.9%                     9.8%             11.9%   \n",
       "2017                    13.3%                     9.9%             12.0%   \n",
       "2018                     nan%                     nan%              nan%   \n",
       "\n",
       "     水利、环境和公共设施管理业城镇单位就业人员平均工资(元) 交通运输、仓储和邮政业城镇单位就业人员平均工资(元)  \\\n",
       "2004                         9.4%                      14.7%   \n",
       "2005                        11.2%                      15.7%   \n",
       "2006                         9.1%                      15.3%   \n",
       "2007                        17.6%                      15.7%   \n",
       "2008                        14.8%                      14.8%   \n",
       "2009                         9.7%                      10.2%   \n",
       "2010                        10.3%                      14.6%   \n",
       "2011                        13.0%                      16.3%   \n",
       "2012                        12.0%                      13.4%   \n",
       "2013                        11.7%                       8.6%   \n",
       "2014                         8.5%                       9.4%   \n",
       "2015                        11.0%                       8.5%   \n",
       "2016                         9.7%                       7.0%   \n",
       "2017                         9.4%                       8.9%   \n",
       "2018                         nan%                       nan%   \n",
       "\n",
       "     房地产业城镇单位就业人员平均工资(元) 电力、燃气及水的生产和供应业城镇单位就业人员平均工资(元) 建筑业城镇单位就业人员平均工资(元)  \\\n",
       "2004                8.1%                         16.0%              11.0%   \n",
       "2005                9.7%                         14.9%              12.2%   \n",
       "2006                9.8%                         14.8%              14.5%   \n",
       "2007               17.3%                         17.8%              14.3%   \n",
       "2008               15.5%                         15.1%              14.8%   \n",
       "2009                7.1%                          8.7%              13.8%   \n",
       "2010               11.3%                         13.0%              13.9%   \n",
       "2011               19.4%                         11.4%              16.6%   \n",
       "2012                9.2%                         10.4%              13.6%   \n",
       "2013                9.2%                         15.3%              15.3%   \n",
       "2014                8.9%                          9.3%               8.9%   \n",
       "2015                8.4%                          7.6%               6.7%   \n",
       "2016                8.7%                          6.3%               6.5%   \n",
       "2017                5.8%                          7.7%               6.7%   \n",
       "2018                nan%                          nan%               nan%   \n",
       "\n",
       "     住宿和餐饮业城镇单位就业人员平均工资(元) 批发和零售业城镇单位就业人员平均工资(元) 采矿业城镇单位就业人员平均工资(元)  \\\n",
       "2004                 12.7%                 19.4%              23.1%   \n",
       "2005                 10.0%                 17.2%              21.9%   \n",
       "2006                  9.8%                 16.6%              18.0%   \n",
       "2007                 11.9%                 18.4%              16.8%   \n",
       "2008                 13.3%                 22.5%              21.5%   \n",
       "2009                  8.0%                 12.9%              11.1%   \n",
       "2010                 12.1%                 15.4%              16.2%   \n",
       "2011                 17.6%                 20.9%              18.2%   \n",
       "2012                 13.8%                 14.0%               9.0%   \n",
       "2013                  8.9%                  8.6%               5.6%   \n",
       "2014                  9.5%                 11.0%               2.6%   \n",
       "2015                  9.5%                  8.0%              -3.7%   \n",
       "2016                  6.3%                  7.8%               1.9%   \n",
       "2017                  5.5%                  9.4%              14.8%   \n",
       "2018                  nan%                  nan%               nan%   \n",
       "\n",
       "     科学研究、技术服务和地质勘查业城镇单位就业人员平均工资(元)  \n",
       "2004                          14.2%  \n",
       "2005                          16.3%  \n",
       "2006                          16.5%  \n",
       "2007                          21.5%  \n",
       "2008                          18.4%  \n",
       "2009                          10.2%  \n",
       "2010                          12.4%  \n",
       "2011                          14.0%  \n",
       "2012                           7.8%  \n",
       "2013                          10.6%  \n",
       "2014                           7.4%  \n",
       "2015                           8.7%  \n",
       "2016                           8.1%  \n",
       "2017                          11.6%  \n",
       "2018                           nan%  "
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prior_cols = ['城镇单位就业人员平均工资(元)',\n",
    "              '信息传输、计算机服务和软件业城镇单位就业人员平均工资(元)',\n",
    "                              '金融业城镇单位就业人员平均工资(元)',\n",
    "              '卫生、社会保障和社会福利业城镇单位就业人员平均工资(元)',\n",
    "                             '制造业城镇单位就业人员平均工资(元)',\n",
    "                             '农、林、牧、渔业城镇单位就业人员平均工资(元)']\n",
    "prior_cols.extend(list(set(rise.columns) - set(prior_cols)))\n",
    "rise.loc[rise.index >='2004',prior_cols]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                       城镇单位就业人员平均工资(元)\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
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       "      <th>2018</th>\n",
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       "      <th>信息传输、计算机服务和软件业</th>\n",
       "      <td>70918.0</td>\n",
       "      <td>80510.0</td>\n",
       "      <td>90915.0</td>\n",
       "      <td>100845.0</td>\n",
       "      <td>112042.0</td>\n",
       "      <td>122478.0</td>\n",
       "      <td>133150.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>金融业</th>\n",
       "      <td>81109.0</td>\n",
       "      <td>89743.0</td>\n",
       "      <td>99653.0</td>\n",
       "      <td>108273.0</td>\n",
       "      <td>114777.0</td>\n",
       "      <td>117418.0</td>\n",
       "      <td>122851.0</td>\n",
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       "      <th>科学研究、技术服务和地质勘查业</th>\n",
       "      <td>64252.0</td>\n",
       "      <td>69254.0</td>\n",
       "      <td>76602.0</td>\n",
       "      <td>82259.0</td>\n",
       "      <td>89410.0</td>\n",
       "      <td>96638.0</td>\n",
       "      <td>107815.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>电力、燃气及水的生产和供应业</th>\n",
       "      <td>52723.0</td>\n",
       "      <td>58202.0</td>\n",
       "      <td>67085.0</td>\n",
       "      <td>73339.0</td>\n",
       "      <td>78886.0</td>\n",
       "      <td>83863.0</td>\n",
       "      <td>90348.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>卫生、社会保障和社会福利业</th>\n",
       "      <td>46206.0</td>\n",
       "      <td>52564.0</td>\n",
       "      <td>57979.0</td>\n",
       "      <td>63267.0</td>\n",
       "      <td>71624.0</td>\n",
       "      <td>80026.0</td>\n",
       "      <td>89648.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>文化、体育和娱乐业</th>\n",
       "      <td>47878.0</td>\n",
       "      <td>53558.0</td>\n",
       "      <td>59336.0</td>\n",
       "      <td>64375.0</td>\n",
       "      <td>72764.0</td>\n",
       "      <td>79875.0</td>\n",
       "      <td>87803.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>教育</th>\n",
       "      <td>43194.0</td>\n",
       "      <td>47734.0</td>\n",
       "      <td>51950.0</td>\n",
       "      <td>56580.0</td>\n",
       "      <td>66592.0</td>\n",
       "      <td>74498.0</td>\n",
       "      <td>83412.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>租赁和商务服务业</th>\n",
       "      <td>46976.0</td>\n",
       "      <td>53162.0</td>\n",
       "      <td>62538.0</td>\n",
       "      <td>67131.0</td>\n",
       "      <td>72489.0</td>\n",
       "      <td>76782.0</td>\n",
       "      <td>81393.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>公共管理和社会组织</th>\n",
       "      <td>42062.0</td>\n",
       "      <td>46074.0</td>\n",
       "      <td>49259.0</td>\n",
       "      <td>53110.0</td>\n",
       "      <td>62323.0</td>\n",
       "      <td>70959.0</td>\n",
       "      <td>80372.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>交通运输、仓储和邮政业</th>\n",
       "      <td>47078.0</td>\n",
       "      <td>53391.0</td>\n",
       "      <td>57993.0</td>\n",
       "      <td>63416.0</td>\n",
       "      <td>68822.0</td>\n",
       "      <td>73650.0</td>\n",
       "      <td>80225.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>全行业</th>\n",
       "      <td>41799.0</td>\n",
       "      <td>46769.0</td>\n",
       "      <td>51483.0</td>\n",
       "      <td>56360.0</td>\n",
       "      <td>62029.0</td>\n",
       "      <td>67569.0</td>\n",
       "      <td>74318.0</td>\n",
       "      <td>82461.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>批发和零售业</th>\n",
       "      <td>40654.0</td>\n",
       "      <td>46340.0</td>\n",
       "      <td>50308.0</td>\n",
       "      <td>55838.0</td>\n",
       "      <td>60328.0</td>\n",
       "      <td>65061.0</td>\n",
       "      <td>71201.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>采矿业</th>\n",
       "      <td>52230.0</td>\n",
       "      <td>56946.0</td>\n",
       "      <td>60138.0</td>\n",
       "      <td>61677.0</td>\n",
       "      <td>59404.0</td>\n",
       "      <td>60544.0</td>\n",
       "      <td>69500.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>房地产业</th>\n",
       "      <td>42837.0</td>\n",
       "      <td>46764.0</td>\n",
       "      <td>51048.0</td>\n",
       "      <td>55568.0</td>\n",
       "      <td>60244.0</td>\n",
       "      <td>65497.0</td>\n",
       "      <td>69277.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>制造业</th>\n",
       "      <td>36665.0</td>\n",
       "      <td>41650.0</td>\n",
       "      <td>46431.0</td>\n",
       "      <td>51369.0</td>\n",
       "      <td>55324.0</td>\n",
       "      <td>59470.0</td>\n",
       "      <td>64452.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>建筑业</th>\n",
       "      <td>32103.0</td>\n",
       "      <td>36483.0</td>\n",
       "      <td>42072.0</td>\n",
       "      <td>45804.0</td>\n",
       "      <td>48886.0</td>\n",
       "      <td>52082.0</td>\n",
       "      <td>55568.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>水利、环境和公共设施管理业</th>\n",
       "      <td>28868.0</td>\n",
       "      <td>32343.0</td>\n",
       "      <td>36123.0</td>\n",
       "      <td>39198.0</td>\n",
       "      <td>43528.0</td>\n",
       "      <td>47750.0</td>\n",
       "      <td>52229.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>居民服务和其他服务业</th>\n",
       "      <td>33169.0</td>\n",
       "      <td>35135.0</td>\n",
       "      <td>38429.0</td>\n",
       "      <td>41882.0</td>\n",
       "      <td>44802.0</td>\n",
       "      <td>47577.0</td>\n",
       "      <td>50552.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>住宿和餐饮业</th>\n",
       "      <td>27486.0</td>\n",
       "      <td>31267.0</td>\n",
       "      <td>34044.0</td>\n",
       "      <td>37264.0</td>\n",
       "      <td>40806.0</td>\n",
       "      <td>43382.0</td>\n",
       "      <td>45751.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>农、林、牧、渔业</th>\n",
       "      <td>19469.0</td>\n",
       "      <td>22687.0</td>\n",
       "      <td>25820.0</td>\n",
       "      <td>28356.0</td>\n",
       "      <td>31947.0</td>\n",
       "      <td>33612.0</td>\n",
       "      <td>36504.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    2011     2012     2013      2014      2015      2016  \\\n",
       "信息传输、计算机服务和软件业   70918.0  80510.0  90915.0  100845.0  112042.0  122478.0   \n",
       "金融业              81109.0  89743.0  99653.0  108273.0  114777.0  117418.0   \n",
       "科学研究、技术服务和地质勘查业  64252.0  69254.0  76602.0   82259.0   89410.0   96638.0   \n",
       "电力、燃气及水的生产和供应业   52723.0  58202.0  67085.0   73339.0   78886.0   83863.0   \n",
       "卫生、社会保障和社会福利业    46206.0  52564.0  57979.0   63267.0   71624.0   80026.0   \n",
       "文化、体育和娱乐业        47878.0  53558.0  59336.0   64375.0   72764.0   79875.0   \n",
       "教育               43194.0  47734.0  51950.0   56580.0   66592.0   74498.0   \n",
       "租赁和商务服务业         46976.0  53162.0  62538.0   67131.0   72489.0   76782.0   \n",
       "公共管理和社会组织        42062.0  46074.0  49259.0   53110.0   62323.0   70959.0   \n",
       "交通运输、仓储和邮政业      47078.0  53391.0  57993.0   63416.0   68822.0   73650.0   \n",
       "全行业              41799.0  46769.0  51483.0   56360.0   62029.0   67569.0   \n",
       "批发和零售业           40654.0  46340.0  50308.0   55838.0   60328.0   65061.0   \n",
       "采矿业              52230.0  56946.0  60138.0   61677.0   59404.0   60544.0   \n",
       "房地产业             42837.0  46764.0  51048.0   55568.0   60244.0   65497.0   \n",
       "制造业              36665.0  41650.0  46431.0   51369.0   55324.0   59470.0   \n",
       "建筑业              32103.0  36483.0  42072.0   45804.0   48886.0   52082.0   \n",
       "水利、环境和公共设施管理业    28868.0  32343.0  36123.0   39198.0   43528.0   47750.0   \n",
       "居民服务和其他服务业       33169.0  35135.0  38429.0   41882.0   44802.0   47577.0   \n",
       "住宿和餐饮业           27486.0  31267.0  34044.0   37264.0   40806.0   43382.0   \n",
       "农、林、牧、渔业         19469.0  22687.0  25820.0   28356.0   31947.0   33612.0   \n",
       "\n",
       "                     2017     2018  \n",
       "信息传输、计算机服务和软件业   133150.0      NaN  \n",
       "金融业              122851.0      NaN  \n",
       "科学研究、技术服务和地质勘查业  107815.0      NaN  \n",
       "电力、燃气及水的生产和供应业    90348.0      NaN  \n",
       "卫生、社会保障和社会福利业     89648.0      NaN  \n",
       "文化、体育和娱乐业         87803.0      NaN  \n",
       "教育                83412.0      NaN  \n",
       "租赁和商务服务业          81393.0      NaN  \n",
       "公共管理和社会组织         80372.0      NaN  \n",
       "交通运输、仓储和邮政业       80225.0      NaN  \n",
       "全行业               74318.0  82461.0  \n",
       "批发和零售业            71201.0      NaN  \n",
       "采矿业               69500.0      NaN  \n",
       "房地产业              69277.0      NaN  \n",
       "制造业               64452.0      NaN  \n",
       "建筑业               55568.0      NaN  \n",
       "水利、环境和公共设施管理业     52229.0      NaN  \n",
       "居民服务和其他服务业        50552.0      NaN  \n",
       "住宿和餐饮业            45751.0      NaN  \n",
       "农、林、牧、渔业          36504.0      NaN  "
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "income_t = income.loc[income.index>='2011']\n",
    "income_t = income_t.transpose()\n",
    "print(\" \"*22,'城镇单位就业人员平均工资(元)')\n",
    "income_t.index = [x[:x.find('城镇单位就业人员平均工资(元)')] for x in income_t.index]\n",
    "income_t.index = [\"全行业\" if x == \"\" else x for x in income_t.index]\n",
    "income_t.sort_values('2017', ascending = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 医疗行业什么时候超过IT\n",
    "在美国等发达国家，医疗行业收入是比IT要高的。咱们来分析一下中国的情况。\n",
    "根据2011年到2017年的涨幅，以及2017年的基数预测，将来多少年之后医疗可以赶上IT。结论是大概2048年。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/matplotlib/font_manager.py:1328: UserWarning: findfont: Font family ['sans-serif'] not found. Falling back to DejaVu Sans\n",
      "  (prop.get_family(), self.defaultFamily[fontext]))\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "yishengRate = 2.228276 \n",
    "ITRate = 2.066391\n",
    "yishengBase = 89648.0\n",
    "ITBase = 133150.0\n",
    "def f(base, rate, year):\n",
    "    return base * rate **(year/6)\n",
    "count = 35\n",
    "yisheng = [f(yishengBase, yishengRate, n) for n in range(count)]\n",
    "IT = [f(ITBase, ITRate, n) for n in range(count)]\n",
    "year = [2017 + n for n in range(count)]\n",
    "plt.plot(year, yisheng)\n",
    "plt.plot(year, IT)\n",
    "plt.legend(['yisheng', 'IT'])\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
